物件導向軟體之架構(Object-Oriented Software Construction)探討

A Study of Teams: How It All Began The Apollo Syndrome Teams Containing Similar Personalities Identifying further Team Roles Team Leadership The Missing Team Roles Developing an inventory Unsuccessful teams Winning teams Ideal team size Features of good members of a team Teams in Public Affairs How Belbin reports developed Case Studies in Using Belbin

Management teams: Why they succeed or fail

Software engineering: theory and practice

Technical debt is a metaphor introduced by Cunningham to indicate “not quite right code which we postpone making it right”. One noticeable symptom of technical debt is represented by code smells, defined as symptoms of poor design and implementation choices. Previous studies showed the negative impact of code smells on the comprehensibility and maintainability of code. While the repercussions of smells on code quality have been empirically assessed, there is still only anecdotal evidence on when and why bad smells are introduced, what is their survivability , and how they are removed by developers. To empirically corroborate such anecdotal evidence, we conducted a large empirical study over the change history of 200 open source projects. This study required the development of a strategy to identify smell-introducing commits, the mining of over half a million of commits, and the manual analysis and classification of over 10K of them. Our findings mostly contradict common wisdom, showing that most of the smell instances are introduced when an artifact is created and not as a result of its evolution. At the same time, 80 percent of smells survive in the system. Also, among the 20 percent of removed instances, only 9 percent are removed as a direct consequence of refactoring operations.

When and Why Your Code Starts to Smell Bad (and Whether the Smells Go Away)

Context: Code smells are assumed to indicate bad design that leads to less maintainable code. However, this assumption has not been investigated in controlled studies with professional software developers. Aim: This paper investigates the relationship between code smells and maintenance effort. Method: Six developers were hired to perform three maintenance tasks each on four functionally equivalent Java systems originally implemented by different companies. Each developer spent three to four weeks. In total, they modified 298 Java files in the four systems. An Eclipse IDE plug-in measured the exact amount of time a developer spent maintaining each file. Regression analysis was used to explain the effort using file properties, including the number of smells. Result: None of the 12 investigated smells was significantly associated with increased effort after we adjusted for file size and the number of changes; Refused Bequest was significantly associated with decreased effort. File size and the number of changes explained almost all of the modeled variation in effort. Conclusion: The effects of the 12 smells on maintenance effort were limited. To reduce maintenance effort, a focus on reducing code size and the work practices that limit the number of changes may be more beneficial than refactoring code smells.

Quantifying the Effect of Code Smells on Maintenance Effort

Code smells are manifestations of design flaws that can degrade code maintainability. As such, the existence of code smells seems an ideal indicator for maintainability assessments. However, to achieve comprehensive and accurate evaluations based on code smells, we need to know how well they reflect factors affecting maintainability. After identifying which maintainability factors are reflected by code smells and which not, we can use complementary means to assess the factors that are not addressed by smells. This paper reports on an empirical study that investigates the extent to which code smells reflect factors affecting maintainability that have been identified as important by programmers. We consider two sources for our analysis: (1) expert-based maintainability assessments of four Java systems before they entered a maintenance project, and (2) observations and interviews with professional developers who maintained these systems during 14 working days and implemented a number of change requests.

Do code smells reflect important maintainability aspects

Code smells are a well-known metaphor to describe symptoms of code decay or other issues with code quality which can lead to a variety of maintenance problems. Even though code smell detection and removal has been well-researched over the last decade, it remains open to debate whether or not code smells should be considered meaningful conceptualizations of code quality issues from the developer's perspective. To some extent, this question applies as well to the results provided by current code smell detection tools. Are code smells really important for developers? If they are not, is this due to the lack of relevance of the underlying concepts, due to the lack of awareness about code smells on the developers' side, or due to the lack of appropriate tools for code smell analysis or removal? In order to align and direct research efforts to address actual needs and problems of professional developers, we need to better understand the knowledge about, and interest in code smells, together with their perceived criticality. This paper reports on the results obtained from an exploratory survey involving 85 professional software developers.

Do developers care about code smells? An exploratory survey

Code smells are indicators of issues with source code quality that may hinder evolution While previous studies mainly focused on the effects of individual code smells on maintainability, we conjecture that not only the individual code smells but also the interactions between code smells affect maintenance We empirically investigate the interactions amongst 12 code smells and analyze how those interactions relate to maintenance problems Professional developers were hired for a period of four weeks to implement change requests on four medium-sized Java systems with known smells On a daily basis, we recorded what specific problems they faced and which artifacts were associated with them Code smells were automatically detected in the pre-maintenance versions of the systems and analyzed using Principal Component Analysis (PCA) to identify patterns of co-located code smells Analysis of these factors with the observed maintenance problems revealed how smells that were co-located in the same artifact interacted with each other, and affected maintainability Moreover, we found that code smell interactions occurred across coupled artifacts, with comparable negative effects as same-artifact co-location We argue that future studies into the effects of code smells on maintainability should integrate dependency analysis in their process so that they can obtain a more complete understanding by including such coupled interactions

Exploring the impact of inter-smell relations on software maintainability: an empirical study

Context: Code smells are indicators of poor coding and design choices that can cause problems during software maintenance and evolution. Objective: This study is aimed at a detailed investigation to which extent problems in maintenance projects can be predicted by the detection of currently known code smells. Method: A multiple case study was conducted, in which the problems faced by six developers working on four different Java systems were registered on a daily basis, for a period up to four weeks. Where applicable, the files associated to the problems were registered. Code smells were detected in the pre-maintenance version of the systems, using the tools Borland Together and InCode. In-depth examination of quantitative and qualitative data was conducted to determine if the observed problems could be explained by the detected smells. Results: From the total set of problems, roughly 30% percent were related to files containing code smells. In addition, interaction effects were observed amongst code smells, and between code smells and other code characteristics, and these effects led to severe problems during maintenance. Code smell interactions were observed between collocated smells (i.e., in the same file), and between coupled smells (i.e., spread over multiple files that were coupled). Conclusions: The role of code smells on the overall system maintainability is relatively minor, thus complementary approaches are needed to achieve more comprehensive assessments of maintainability. Moreover, to improve the explanatory power of code smells, interaction effects amongst collocated smells and coupled smells should be taken into account during analysis.

Aiko Yamashita

Papers

Do code smells reflect important maintainability aspects

Do developers care about code smells? An exploratory survey

Exploring the impact of inter-smell relations on software maintainability: an empirical study

To what extent can maintenance problems be predicted by code smell detection? - An empirical study

Code smells as system-level indicators of maintainability: An empirical study